A Robust and Efficient Machine Learning Framework for Enhancing Early Detection of Android Malware by Fandi Kurniawan, Deris Stiawan, Darius Antoni, Mohd Yazid Idris, Rahmat Budiarto

“…The advancement of information technology has introduced new challenges in cybersecurity, especially related to the Android platform which is the main target of malicious software (malware) attacks. …”
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Island Partitioning of Smart Distribution Systems in Emergencies Considering Voltage and Frequency Stability by Zahra Hosseini Najafabadi, Asghar Akbari Foroud

“…Immediately after the disconnection of the main grid due to a fault, the island subsystem experiences intense voltage and frequency deviations. …”
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SMART: unique splitting-while-merging framework for gene clustering. by Rui Fa, David J Roberts, Asoke K Nandi

“…Based on the performance of many metrics, all numerical results show that SMART is superior to compared existing self-splitting algorithms and traditional algorithms. Three main properties of the proposed SMART framework are summarized as: (1) needing no parameters dependent on the respective dataset or a priori knowledge about the datasets, (2) extendible to many different applications, (3) offering superior performance compared with counterpart algorithms.…”
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Rolling Bearing Fault Diagnosis Using a Deep Convolutional Autoencoding Network and Improved Gustafson–Kessel Clustering by Yaochun Wu, Rongzhen Zhao, Wuyin Jin, Linfeng Deng, Tianjing He, Sencai Ma

“…A novel method based on a deep convolutional autoencoding network (DCAEN) and adaptive nonparametric weighted-feature extraction Gustafson–Kessel (ANW-GK) clustering algorithm was developed for the fault diagnosis of bearings. …”
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Formation of a dynamic knowledge base of fuzzy inference systems for estimating changing in time objects by A. Kostikova, N. Skiter

“…The article is a continuation of a series of author`s papers of dynamic fuzzy sets, which the main purpose is to process various information about the objects of complex systems represented by dynamic fuzzy descriptions. …”
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Determination of agricultural land use: incidence of atmospheric corrections and the implementation in multi-sensor and multi-temporal images by E. Willington, J. P. Clemente, M. Bocco

“…The two supervised classification algorithms used were neural networks and maximum likelihood. …”
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Steam Generator for Hydrothermal Treatment of Agricultural Equipment by V. A. Gusarov, L. Yu. Yuferev

“…(Materials and methods) The paper describes the algorithm of the steam generator operation and presents its main technical characteristics and the design diagram. …”
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Machine learning approach for revealing the nickel grade and recovery optimization in reduction process of laterite ores by Vuri Ayu Setyowati, Fakhreza Abdul

“…With the increasing demand for energy-efficient processes, the selective reduction of laterite nickel ore, followed by ferronickel metal separation, has become the main focus. Researchers have studied and published many process variables or features to date. …”
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Child Psychiatry Engagement in the Management of Delirium in Critically Ill Children by Sean S. Barnes, Marco A. Grados, Sapna R. Kudchadkar

“…To characterize the engagement of child psychiatry by pediatric intensivists in cases of suspected delirium in a pediatric intensive care unit (PICU) prior to implementation of a delirium management algorithm with regards to recommendations, antipsychotic prescribing, and follow-up after PICU discharge. …”
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Robo-advisor enablers and inhibitors: A dual-factor framework and a benefit-risk model integration for understanding customer acceptance by Sindhu Singh, Bhargavi Karamcheti

“…Despite these inherent strengths, the penetration of these algorithm-driven platforms has continued to be suboptimal. …”
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Pemodelan Sistem Monitoring Kualitas Udara Pintar Berbasis Internet of Things dengan Pendekatan Machine Learning by Eddy Prasetyo Nugroho, Ani Anisyah, Deva Shofa Al Fathin, Muhammad Nur Yasin Amadudin, Muhammad Satria Ramadhani, Yosafat

“…The combination of the real-time sensor and the LSTM algorithm resulted in an air quality prediction accuracy rate of 88%. …”
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Performance analysis of advanced deep learning technics: Application to solar energy forecasting and management in several cities in Chad by Osée Mounkang, Claude Vidal Aloyem Kaze, Nzoko Tayo Dieudonné, Ghislain Junior Bangoup Ntegmi, Duclair Paul Edouard Pountounynyi, Hervice Roméo Fogno Fotso, Armel Zambou Kenfack, Germaine Kenmoe Djuidje, René Tchinda

“…To achieve this, eight deep learning algorithms were used to optimize energy management. …”
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Monitoring soil salinization in Arid cotton fields using Unmanned Aerial Vehicle hyperspectral imagery by Jinming Zhang, Jianli Ding, Jiao Tan, Jinjie Wang, Zihan Zhang, Zeyuan Wang, Xiangyu Ge

“…Soil salinization is one of the main causes of low yield in cotton fields, leading to soil compaction and significantly affecting crop growth and nutrient absorption. …”
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Improving the level of training of IT-specialists based on analysis of labor market requirements by A. V. Gavrilov, S. V. Kulikova, G. E. Golkina

“…The article discusses a comprehensive methodology for collecting and analyzing information collected from the websites of recruiting companies, including: 1) an algorithm for determining the competencies of IT specialists most in demand by employers; 2) a database model for storing information about vacancies; 3) an algorithm for bringing unstructured textual information about a vacancy to a factual database; 4) authoring analytical application based on the Qlik Sence BI system, which allows monitoring vacancies. …”
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Genotype Prediction from Retinal Fundus Images Using Deep Learning in Eyes with Age-Related Macular Degeneration by Avishai Halev, PhD, Denis Huang, MD, Shahbaz Rezaei, PhD, Sean Banks, BS, John D. McPherson, PhD, Suma P. Shankar, MD, PhD, Xin Liu, PhD, Glenn Yiu, MD, PhD

“…Design: Deep learning algorithm development to classify single-nucleotide polymorphism in the complement factor H (CFH) and age-related maculopathy susceptibility 2 (ARMS2) genes using retinal fundus images. …”
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Technology features of decellularization of human liver fragments as tissue-specific fine-grained matrix for cell-engineering liver construction by E. A. Nemets, L. A. Kirsanova, Ju. B. Basok, M. Ju. Schagidulin, E. A. Volkova, S. T. Metelsky, V. I. Sevastianov

“…On the basis of the experimental results obtained the algorithm of preliminary study of donor human liver designed to optimize the process of obtaining decellularization fragments of liver tissue was elaborated.Conclusion. …”
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Electric Submersible Pump Fault Diagnosis Based on Laplacian Eigenmaps and Weighted Extreme Learning Machine by XU Zekun, FU Jun, GAO Xiaoyong, ZHANG Yu, LI Qiang, TAN Chaodong

“…At present, ESP fault diagnosis mainly depends on the experience of field technicians, and automatic diagnosis and analysis cannot be done quickly and timely. …”
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A Machine Learning Approach to Evaluate the Performance of Rural Bank by Jun Wei, Tao Ye, Zhe Zhang

“…On the other hand, they mainly focus on causal inference and lack systematic quantitative conclusions from the perspective of prediction. …”
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Energy-Aware Task Allocation for Multi-Cloud Networks by Sambit Kumar Mishra, Sonali Mishra, Ahmed Alsayat, N Z Jhanjhi, Mamoona Humayun, Kshira Sagar Sahoo, Ashish Kr. Luhach

“…However, the average energy consumption improved through <italic>ETAMCN</italic> is approximately 14&#x0025;, 6.3&#x0025;, and 2.8&#x0025; in opposed to the random allocation algorithm, Cloud Z-Score Normalization (<italic>CZSN</italic>) algorithm, and multi-objective scheduling algorithm with Fuzzy resource utilization (FR-MOS), respectively. …”
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Comparative Effectiveness of Early and Delayed Surgical Interventions in Patients with Acute Adhesive Intestinal Obstruction: A Multicenter Controlled Randomized Trial Prospective... by B. V. Sigua, A. E. Demko, S. V. Petrov, P. A. Kotkov, I. A. Soloviev, A. V. Vovk, A. V. Osipov, V. I. Serdyuk, D. A. Chernyshev, M. A. Protchenkov, I. I. Gubkov, M. G. Zaitsev, S. Yu. Puzanov, A. A. Kozobin, O. V. Babkov, A. V. Glebova, D. S. Sakhno, D. V. Gurzhiy, V. P. Zemlyanoy

“…During the implementation of the algorithm of actions, it was possible to achieve non-surgical resolution of AAIO phenomena in 86 patients (73.5%) of the main group, which, although statistically insignificant, exceeded the similar indicator of the comparison group, where successful conservative measures were carried out in 61 patients (61.6%) (χ2=3.48, p=0.06). …”
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